An analysis of Exit Polls, True Votes and Cumulative Vote Shares indicates that the 2014 Governor elections in Wisconsin, Florida, Illinois and Maryland were likely stolen.

Although most voters believe that politicians are corrupt, many still cling to the myth that votes are accurately and fairly counted – and that election fraud is a conspiracy theory.

Many voters are still unaware that the unadjusted, pristine exit polls are routinely adjusted to match the recorded vote. The implicit assumption is that the recorded vote represents true voter intent.
Mathematical analysis of discrepancies between unadjusted presidential state and national exit polls versus recorded votes from 1988-2008 confirms systemic fraud to a 100% probability. For a suspicious election, mathematical analysis is a useful way to determine the likelihood of fraud.

Pre-election polls
To set the context,Democrats do much better in Registered Voter (RV) polls than in the Likely Voter (LV) subsets. The reason is simple: voters considered unlikely to vote (mostly newly registered Democrats) are eliminated from the full RV sample. The RV polls are often close to the unadjusted exit polls and the True Vote. On the othr hand, final LV polls published on Election eve are excellent predictors of the bogus final recorded vote.

In each of the 1988, 1992, 2004 and 2008 presidential elections, in order for the pollsters to force the unadjusted exit polls to match the recorded vote, they needed to assume an impossible number of returning Republican voters. In the 1988-2008 presidential elections, the Democrats led the average recorded vote by 48-46%. But they led by 52-42% in the unadjusted state and national exit polls and the True Vote Model. The 8% margin discrepancy was far beyond the margin of error. But the discrepancy was not due to poor polling design, or exit poll respondents lying about their past vote, their current vote. They would have to lie in response to every one of dozens of questions.

But fraud is not limited to presidential elections. House, senate, governor and local elections have also been compromised by maliciously coded voting machines and voter disenfranchisement.

Who will argue with these points?
1- Unadjusted exit polls are hidden from the public.
2- Unadjusted exit polls are adjusted to match the recorded vote.
3- Voting machine software is proprietary, not open to public viewing
4- Auditing and hand-counting of votes are denied.

Exit polls
Since we cannot view unadjusted exit polls until years later (if at all), we are left with final, adjusted polls. The question “How did you vote in the last election” is no longer asked by the pollsters. An exhaustive analysis of 1988-2008 presidential election unadjusted state and national exit polls shows why the question is no longer asked: it gives an analyst the ability to check the number of returning voters from the prior election. The number provided in the adjusted polls has often proved to be impossible. There were more returning Bush voters in 1992, 2004 and 2008 than were alive. The 2004 election is a case in point. Simple arithmetic proves that it was stolen. It is a fact that…
1- Bush had 50.5 million recorded votes in 2000.
2- The 2004 National Exit Poll indicates that there were 52.6 million returning Bush 2000 voters. This is obviously impossible; the pollsters had to adjust the number of returning voters to match the 2004 recorded vote.
3- Of the 50.5 million Bush 2000 voters, approximately 2 million died before the 2004 election.
4- Approximately one million Bush 2000 voters did not return in 2004.
Therefore, an estimated 47.5 million Bush 2000 voters returned in 2004. Simple arithmetic shows there had to be at least 5 million (52.6-47.5) phantom Bush 2004 voters.https://richardcharnin.wordpress.com/2012/04/05/fixing-the-exit-polls-to-match-the-policy/

We are forced to analyze adjusted exit polls to look for anomalies. Party-ID is a demographic we can check in lieu of the past vote question. Of course, there is no way to check the Party-ID mix mathematically as we can with the past vote. But it is still useful to see if the percentage mix and corresponding vote shares are plausible based on voter registration and prior elections.

In 2010, Sink (D) won the unadjusted exit poll by 50.8-45.4% (280,000 votes).There were 3150 respondents (2% margin of error). Of course, the poll was adjusted to match Scott’s 49.6-48.4% recorded 64,000 vote margin. It indicated that 47% of the voters were returning Obama voters and 47% McCain voters. But Obama won the Florida easily. Scott needed 67% of the other 6% who voted (new voters and others who voted for third parties in 2008). These adjustments are highly implausible.

To match the recorded vote, the pollsters assumed a 36D-36R-28I split with Scott winning Independents by 52-44%. In matching the unadjusted exit poll, Sink required a 38D-34R-28I split while winning Independents by 47-43%.

The 2014 election was virtually a carbon copy of 2010. Scott won by 48.2-47.1% (66,000 votes). Crist had 52% of the 2-party True Vote if Sink had the 52.2% share in the unadjusted 2010 exit poll. There were 500,000 more voters than in 2010. Historically, heavy voter turnout is good for the Democrats.

So how did Crist lose by 1%?

Crist did not lose. To match the recorded vote, the pollsters assumed an implausible Party-ID split: 31D- 35R- 34I. Assuming the true mix was 35D- 35R- 30I, Crist won by 181,000 votes (49.2-46.1%). According to the adjusted exit poll (assumed biased for Scott), Crist had 91% of Democrats; Scott had just 88% of Republicans. Crist won Independents by 46-44%. Crist shares were most likely higher.

Party-ID was 36D- 37R- 27I, as opposed to 39D- 35R- 27I in prior elections. There was heavy voter turnout. Burke had just 43% of Independents. If the mix was actually 38D- 35R- 27I and Burke had 50% of independents, she would have been a 50.2-48.5% winner.

National Exit Poll (House)
The mix was 35D- 36R- 28I. The Republicans won by 52.0-45.8%. The Democrats had an implausibly low 42% of Independents. If the mix was 36D- 36R- 28I and the Democrats had 50% of the Independents, it would have been a virtual 49% tie.

Cumulative Vote Shares

It is well known fact that Democrats are the majority in highly populated urban locations; Republicans are heavily represented in rural areas. Highly populated precincts are mostly Democratic. But in scores of state elections there has been an increase in cumulative Republican vote shares in larger precincts. This anomaly has been confirmed by PhDs in Kansas and Vanderbilt University.

-All 67 counties: Crist had 47.0% of 5.94 million votes
-12 Top counties: Crist had 52.0% of 3.67 million votes
-55 counties: Crist had 38.9% of 2.27 million votes
Top 12 counties, Crist’s 2-party share declined from 58.5% to 54.4%
Note: precinct data is not available for the 55 counties.

2005 Special Ohio Congressional Election
Michael Collins has written about the GOP CVS trend in the 2005 Special Ohio congressional election and the 2012 primaries.

“Richard Charnin, posting as TruthIsAll, first noted the pattern with an analysis of the 2005 special election for a vacated seat for Ohio’s 2nd district, in the House of Representatives. The candidates were the liberal-populist Democrat Paul Hackett versus a right-wing Republican, Jean Schmidt. Charnin noticed that Schmidt’s votes and percentages increased substantially from the smallest to largest precincts in that district. This was a patently absurd pattern of vote accumulation since the liberal Hackett wins were in highly conservative counties that rarely voted for any Democrat.

Precincts with the most votes favored Schmidt at nearly 100%, with Hackett winning in only those with less than 200 votes counted. A review of precinct level results by Richard Charnin (TruthIsAll on Democratic Underground) reveals this interesting trend. This data is preliminary and more detail needs to be obtained from the Clermont Board of Elections. However, the trend observed for Clermont makes little sense on the face of it.

Hackett won 38 of 191 Clermont precincts with fewer than 187 votes, but lost ALL of the largest 54 precincts (those with more than 187 votes each). This is reflected in the following graph produced by Democratic Underground poster TruthIsAll, one of the first election fraud analysts to notice anomalies in Clermont County.

Hackett won 38 of 191 Clermont precincts but lost the 54 largest.

The following percentages help elaborate the graph above.
Hackett’s percentage by precinct group size:
46.9% in precincts under 100 votes
43.5% in precincts of 100-200 votes
39.6% in precincts of 200-300 votes
34.6% in precincts of 300 + votes

“Aside from the vote counting irregularities, other questions remain. Democrats typically do poorly in rural areas. A city-based attorney who supports the right to choose and refuses to support gay bashing legislation, who calls the President a “chicken hawk” and a “son of a bitch”, this candidate, Paul Hackett, carried the four most rural counties in District 2 by an average 59% to 41% margin. Yet this candidate failed in the more populous areas, where he would be expected to do better”.

These results raise interesting questions. Why does Hackett do much better in the smaller precincts? Are they more rural than the larger precincts? If so, does this not present a counterintuitive pattern, with the Democrat taking some of the conservative, less populated areas and the Republican winning all of the precincts in the most populated areas?

A question can be raised about the difference between turnout (the votes cast) and the actual size of the precinct, which may or may not be a reflection of votes cast. The following graph, also produced by TruthIsAll, answers the question. As he said while commenting on this data on 8/5/05: “The regression line has zero slope. Voters turned out at a fairly constant rate across precincts. So turnout wasn’t a factor in explaining why the Schmidt vote percentage increased as precinct size increased.”

Voter turnout in the larger precincts in Clermont County matches that in the overall 2nd District. Hackett sweeps rural, lower-income areas, while Schmidt takes those wealthier, more populous.

No Correlation between Precinct Registration and Voter Turnout

On the face of it, this is odd. The demographic blue-red maps for the 2004 election showed a positive correlation between population density and Democratic (Kerry) votes. Yet in the 2nd District of Ohio in 2005, the exact opposite was true.

Hackett dominated the least populated areas of the district, while Schmidt prevailed in the more populated areas. One observer said that Hackett performed as strongly as he did in rural District 2 because his handgun carry permit was publicized. This ignores the fact that the National Rifle Association endorsed Schmidt; it also ignores the generally prevailing positive attitude towards gun ownership in Southwest Ohio. This argument has one major problem. The NRA has one of the most disciplined political operations in the country. The members are consistent in following endorsements. The endorsement of Schmidt by NRA did not mean “think about voting for Schmidt” it meant “vote Schmidt.” Opposition from the NRA is a major impediment in rural areas.

2012 primaries
Consistent CVS anomalies in the 2012 GOP primaries favored Romney
Michael Collins wrote about it in a two-part article:
“Part I of this series suggested that there may well have been massive vote flipping for candidate Mitt Romney in the Republican primaries (Rigged Elections for Romney (10/22/12) The article and the initial research analysis were received broadly. In addition, highly motivated citizens across the country and a team of high school students contacted the authors for help replicating the research in their states. The researchers, Francois Choquet et al., point out that this can be done with their open source techniques.

The basic argument is straightforward. If you look at precinct level voting data arranged from the smallest to the largest precincts, you will see Romney’s gains increasing substantially as the cumulative vote increases. For example, Ohio and Wisconsin show this clearly as do eleven other states presented here. This extraordinary vote gain from smallest to largest precincts is so out of line, that the probability that this would happen by chance alone is often less than 1 out of a number represented by 1 preceded by 100 zeros and a decimal point, a value beneath the statistical package’s lower limits. As a result, the researchers termed the suspected vote flipping for Romney the “amazing anomaly.” (The Amazing Statistical Anomaly)

The research team’s observation of Romney gains based on precinct size is not unique. The anomaly was raised previously concerning the Republican presidential primaries on a political discussion forum.